Streami: An MPI Data-Parallel Library to Compute Field Lines on GPUs

2026-05-29

AI Summary

This work proposes a lightweight and scalable GPU-accelerated library designed to meet the demand for efficient streamline tracing in large-scale computational fluid dynamics simulations. Built upon an MPI-based data-parallel framework and featuring a modular API, the library supports diverse flow field representations and seamlessly integrates into existing MPI applications for both post hoc and in situ analysis. By innovatively combining GPU acceleration with distributed-memory architectures, the approach achieves high-performance streamline computation while also providing an interactive prototype tool for seed point placement to facilitate rapid visualization development. The code is released under a permissive open-source license, balancing performance, flexibility, and usability.

Abstract

We present Streami, an extensible GPU-accelerated library for the computation of field lines in fluid flows on high-performance computers. Streami acts as a thin layer used for both post-hoc or in-situ analysis and can interface with existing MPI applications. We discuss Streami's application programming interface, key design decisions that led to Streami's high performance and extensibility, as well as extensions to support different fluid flow field representations. We also present a sample application for rapid prototyping and interactive seed point placement. Streami is released under a permissive open-source software license.

Problem

• field lines
• fluid flows
• GPU acceleration
• high-performance computing
• MPI

Innovation

• GPU acceleration
• MPI
• field line computation
• in-situ analysis
• data-parallel library